title: Registration of abdominal tumor DCE-MRI data based on deconvolution of joint statistics.
abstract: The analysis of Dynamic Contrast Enhanced Magnetic Resonance Imaging (DCE-MRI) data of body tumors presents several challenges. The accumulation of contrast agent in tissues results in a temporally varying contrast in an image series. At the same time, the body regions are subject to potentially extensive motion mainly due to breathing, heart beat, and peristalsis. This complicates any further automated analysis of a DCE-MRI time series such as for tumor lesion segmentation and volumetry. To address this problem we propose a novel effective non-rigid registration method based on the restoration of the joint statistics of pairs of images in the time series. Every image in the time series is registered to a reference one from the contrast enhanced phase. The pairwise registration is performed with deconvolution of the joint statistics, forcing the results back to the spatial domain and regularizing them with Gaussian spatial smoothing. The registration method has been validated with both a simulated phantom as well as real datasets with improved results for both its accuracy and efficiency.
authors.forename: David
authors.initials: D
authors.lastname: Pilutti
authors.forename: Martin
authors.initials: M
authors.lastname: Büchert
authors.forename: Stathis
authors.initials: S
authors.lastname: Hadjidemetriou
mesh_terms: D000008:Abdominal Neoplasms / Q000175:diagnosis*; D000465:Algorithms; D003198:Computer Simulation; D003287:Contrast Media; D006801:Humans; D007091:Image Processing, Computer-Assisted; D008099:Liver / Q000473:pathology; D008168:Lung / Q000473:pathology; D008279:Magnetic Resonance Imaging / Q000379:methods*; D019047:Phantoms, Imaging; D013997:Time Factors
chemical_list: D003287:Contrast Media